Encoding data for storage in a dispersed storage network

ABSTRACT

A method for execution by a dispersed storage and task (DST) processing unit that includes a processor includes receiving a data object for storage in the DSN via a network. Available storage unit data is generated, indicating a subset of a plurality of storage units of the DSN that corresponds to a plurality of available storage units. A shortened encoding matrix is generated based on an original encoding matrix and the available storage unit data. A size of the shortened encoding matrix is based on a number of storage units in the plurality of available storage units. A plurality of encoded slices is generated, each for transmission to one of the plurality of available storage units via the network, by performing an encoding function on the shortened encoding matrix and the data obj ect.

CROSS-REFERENCE TO RELATED APPLICATIONS

The present U.S. Utility Patent Application claims priority pursuant to35 U.S.C. §119(e) to U.S. Provisional Application No. 62/211,975,entitled “STORING ENCODED DATA SLICES IN A DISPERSED STORAGE NETWORK”,filed Aug. 31, 2015, which is hereby incorporated herein by reference inits entirety and made part of the present U.S. Utility PatentApplication for all purposes.

STATEMENT REGARDING FEDERALLY SPONSORED RESEARCH OR DEVELOPMENT

Not applicable.

INCORPORATION-BY-REFERENCE OF MATERIAL SUBMITTED ON A COMPACT DISC

Not applicable.

BACKGROUND OF THE INVENTION

Technical Field of the Invention

This invention relates generally to computer networks and moreparticularly to dispersing error encoded data.

Description of Related Art

Computing devices are known to communicate data, process data, and/orstore data. Such computing devices range from wireless smart phones,laptops, tablets, personal computers (PC), work stations, and video gamedevices, to data centers that support millions of web searches, stocktrades, or on-line purchases every day. In general, a computing deviceincludes a central processing unit (CPU), a memory system, userinput/output interfaces, peripheral device interfaces, and aninterconnecting bus structure.

As is further known, a computer may effectively extend its CPU by using“cloud computing” to perform one or more computing functions (e.g., aservice, an application, an algorithm, an arithmetic logic function,etc.) on behalf of the computer. Further, for large services,applications, and/or functions, cloud computing may be performed bymultiple cloud computing resources in a distributed manner to improvethe response time for completion of the service, application, and/orfunction. For example, Hadoop is an open source software framework thatsupports distributed applications enabling application execution bythousands of computers.

In addition to cloud computing, a computer may use “cloud storage” aspart of its memory system. As is known, cloud storage enables a user,via its computer, to store files, applications, etc. on an Internetstorage system. The Internet storage system may include a RAID(redundant array of independent disks) system and/or a dispersed storagesystem that uses an error correction scheme to encode data for storage.

BRIEF DESCRIPTION OF THE SEVERAL VIEWS OF THE DRAWING(S)

FIG. 1 is a schematic block diagram of an embodiment of a dispersed ordistributed storage network (DSN) in accordance with the presentinvention;

FIG. 2 is a schematic block diagram of an embodiment of a computing corein accordance with the present invention;

FIG. 3 is a schematic block diagram of an example of dispersed storageerror encoding of data in accordance with the present invention;

FIG. 4 is a schematic block diagram of a generic example of an errorencoding function in accordance with the present invention;

FIG. 5 is a schematic block diagram of a specific example of an errorencoding function in accordance with the present invention;

FIG. 6 is a schematic block diagram of an example of a slice name of anencoded data slice (EDS) in accordance with the present invention;

FIG. 7 is a schematic block diagram of an example of dispersed storageerror decoding of data in accordance with the present invention;

FIG. 8 is a schematic block diagram of a generic example of an errordecoding function in accordance with the present invention;

FIG. 9 is a schematic block diagram of an embodiment of a dispersed ordistributed storage network (DSN) in accordance with the presentinvention;

FIG. 10 is a schematic block diagram of a specific example of an errorencoding function in accordance with the present invention; and

FIG. 11 is a logic diagram of an example of a method of encoding datafor storage in accordance with the present invention.

DETAILED DESCRIPTION OF THE INVENTION

FIG. 1 is a schematic block diagram of an embodiment of a dispersed, ordistributed, storage network (DSN) 10 that includes a plurality ofcomputing devices 12-16, a managing unit 18, an integrity processingunit 20, and a DSN memory 22. The components of the DSN 10 are coupledto a network 24, which may include one or more wireless and/or wirelined communication systems; one or more non-public intranet systemsand/or public interne systems; and/or one or more local area networks(LAN) and/or wide area networks (WAN).

The DSN memory 22 includes a plurality of storage units 36 that may belocated at geographically different sites (e.g., one in Chicago, one inMilwaukee, etc.), at a common site, or a combination thereof. Forexample, if the DSN memory 22 includes eight storage units 36, eachstorage unit is located at a different site. As another example, if theDSN memory 22 includes eight storage units 36, all eight storage unitsare located at the same site. As yet another example, if the DSN memory22 includes eight storage units 36, a first pair of storage units are ata first common site, a second pair of storage units are at a secondcommon site, a third pair of storage units are at a third common site,and a fourth pair of storage units are at a fourth common site. Notethat a DSN memory 22 may include more or less than eight storage units36. Further note that each storage unit 36 includes a computing core (asshown in FIG. 2, or components thereof) and a plurality of memorydevices for storing dispersed error encoded data.

In various embodiments, each of the storage units operates as adistributed storage and task (DST) execution unit, and is operable tostore dispersed error encoded data and/or to execute, in a distributedmanner, one or more tasks on data. The tasks may be a simple function(e.g., a mathematical function, a logic function, an identify function,a find function, a search engine function, a replace function, etc.), acomplex function (e.g., compression, human and/or computer languagetranslation, text-to-voice conversion, voice-to-text conversion, etc.),multiple simple and/or complex functions, one or more algorithms, one ormore applications, etc. Hereafter, a storage unit may be interchangeablyreferred to as a dispersed storage and task (DST) execution unit and aset of storage units may be interchangeably referred to as a set of DSTexecution units.

Each of the computing devices 12-16, the managing unit 18, and theintegrity processing unit 20 include a computing core 26, which includesnetwork interfaces 30-33. Computing devices 12-16 may each be a portablecomputing device and/or a fixed computing device. A portable computingdevice may be a social networking device, a gaming device, a cell phone,a smart phone, a digital assistant, a digital music player, a digitalvideo player, a laptop computer, a handheld computer, a tablet, a videogame controller, and/or any other portable device that includes acomputing core. A fixed computing device may be a computer (PC), acomputer server, a cable set-top box, a satellite receiver, a televisionset, a printer, a fax machine, home entertainment equipment, a videogame console, and/or any type of home or office computing equipment.Note that each managing unit 18 and the integrity processing unit 20 maybe separate computing devices, may be a common computing device, and/ormay be integrated into one or more of the computing devices 12-16 and/orinto one or more of the storage units 36. In various embodiments,computing devices 12-16 can include user devices and/or can be utilizedby a requesting entity generating access requests, which can includerequests to read or write data to storage units in the DSN.

Each interface 30, 32, and 33 includes software and hardware to supportone or more communication links via the network 24 indirectly and/ordirectly. For example, interface 30 supports a communication link (e.g.,wired, wireless, direct, via a LAN, via the network 24, etc.) betweencomputing devices 14 and 16. As another example, interface 32 supportscommunication links (e.g., a wired connection, a wireless connection, aLAN connection, and/or any other type of connection to/from the network24) between computing devices 12 & 16 and the DSN memory 22. As yetanother example, interface 33 supports a communication link for each ofthe managing unit 18 and the integrity processing unit 20 to the network24.

Computing devices 12 and 16 include a dispersed storage (DS) clientmodule 34, which enables the computing device to dispersed storage errorencode and decode data as subsequently described with reference to oneor more of FIGS. 3-8. In this example embodiment, computing device 16functions as a dispersed storage processing agent for computing device14. In this role, computing device 16 dispersed storage error encodesand decodes data on behalf of computing device 14. With the use ofdispersed storage error encoding and decoding, the DSN 10 is tolerant ofa significant number of storage unit failures (the number of failures isbased on parameters of the dispersed storage error encoding function)without loss of data and without the need for a redundant or backupcopies of the data. Further, the DSN 10 stores data for an indefiniteperiod of time without data loss and in a secure manner (e.g., thesystem is very resistant to unauthorized attempts at accessing thedata).

In operation, the managing unit 18 performs DS management services. Forexample, the managing unit 18 establishes distributed data storageparameters (e.g., vault creation, distributed storage parameters,security parameters, billing information, user profile information,etc.) for computing devices 12-14 individually or as part of a group ofuser devices. As a specific example, the managing unit 18 coordinatescreation of a vault (e.g., a virtual memory block associated with aportion of an overall namespace of the DSN) within the DSN memory 22 fora user device, a group of devices, or for public access and establishesper vault dispersed storage (DS) error encoding parameters for a vault.The managing unit 18 facilitates storage of DS error encoding parametersfor each vault by updating registry information of the DSN 10, where theregistry information may be stored in the DSN memory 22, a computingdevice 12-16, the managing unit 18, and/or the integrity processing unit20.

The DSN managing unit 18 creates and stores user profile information(e.g., an access control list (ACL)) in local memory and/or withinmemory of the DSN memory 22. The user profile information includesauthentication information, permissions, and/or the security parameters.The security parameters may include encryption/decryption scheme, one ormore encryption keys, key generation scheme, and/or dataencoding/decoding scheme.

The DSN managing unit 18 creates billing information for a particularuser, a user group, a vault access, public vault access, etc. Forinstance, the DSN managing unit 18 tracks the number of times a useraccesses a non-public vault and/or public vaults, which can be used togenerate a per-access billing information. In another instance, the DSNmanaging unit 18 tracks the amount of data stored and/or retrieved by auser device and/or a user group, which can be used to generate aper-data-amount billing information.

As another example, the managing unit 18 performs network operations,network administration, and/or network maintenance. Network operationsincludes authenticating user data allocation requests (e.g., read and/orwrite requests), managing creation of vaults, establishingauthentication credentials for user devices, adding/deleting components(e.g., user devices, storage units, and/or computing devices with a DSclient module 34) to/from the DSN 10, and/or establishing authenticationcredentials for the storage units 36. Network administration includesmonitoring devices and/or units for failures, maintaining vaultinformation, determining device and/or unit activation status,determining device and/or unit loading, and/or determining any othersystem level operation that affects the performance level of the DSN 10.Network maintenance includes facilitating replacing, upgrading,repairing, and/or expanding a device and/or unit of the DSN 10.

The integrity processing unit 20 performs rebuilding of ‘bad’ or missingencoded data slices. At a high level, the integrity processing unit 20performs rebuilding by periodically attempting to retrieve/list encodeddata slices, and/or slice names of the encoded data slices, from the DSNmemory 22. For retrieved encoded slices, they are checked for errors dueto data corruption, outdated version, etc. If a slice includes an error,it is flagged as a ‘bad’ slice. For encoded data slices that were notreceived and/or not listed, they are flagged as missing slices. Badand/or missing slices are subsequently rebuilt using other retrievedencoded data slices that are deemed to be good slices to produce rebuiltslices. The rebuilt slices are stored in the DSN memory 22.

FIG. 2 is a schematic block diagram of an embodiment of a computing core26 that includes a processing module 50, a memory controller 52, mainmemory 54, a video graphics processing unit 55, an input/output (IO)controller 56, a peripheral component interconnect (PCI) interface 58,an IO interface module 60, at least one IO device interface module 62, aread only memory (ROM) basic input output system (BIOS) 64, and one ormore memory interface modules. The one or more memory interfacemodule(s) includes one or more of a universal serial bus (USB) interfacemodule 66, a host bus adapter (HBA) interface module 68, a networkinterface module 70, a flash interface module 72, a hard drive interfacemodule 74, and a DSN interface module 76.

The DSN interface module 76 functions to mimic a conventional operatingsystem (OS) file system interface (e.g., network file system (NFS),flash file system (FFS), disk file system (DFS), file transfer protocol(FTP), web-based distributed authoring and versioning (WebDAV), etc.)and/or a block memory interface (e.g., small computer system interface(SCSI), internet small computer system interface (iSCSI), etc.). The DSNinterface module 76 and/or the network interface module 70 may functionas one or more of the interface 30-33 of FIG. 1. Note that the IO deviceinterface module 62 and/or the memory interface modules 66-76 may becollectively or individually referred to as IO ports.

FIG. 3 is a schematic block diagram of an example of dispersed storageerror encoding of data. When a computing device 12 or 16 has data tostore it disperse storage error encodes the data in accordance with adispersed storage error encoding process based on dispersed storageerror encoding parameters. Here, the computing device stores data object40, which can include a file (e.g., text, video, audio, etc.), or otherdata arrangement. The dispersed storage error encoding parametersinclude an encoding function (e.g., information dispersal algorithm,Reed-Solomon, Cauchy Reed-Solomon, systematic encoding, non-systematicencoding, on-line codes, etc.), a data segmenting protocol (e.g., datasegment size, fixed, variable, etc.), and per data segment encodingvalues. The per data segment encoding values include a total, or pillarwidth, number (T) of encoded data slices per encoding of a data segmenti.e., in a set of encoded data slices); a decode threshold number (D) ofencoded data slices of a set of encoded data slices that are needed torecover the data segment; a read threshold number (R) of encoded dataslices to indicate a number of encoded data slices per set to be readfrom storage for decoding of the data segment; and/or a write thresholdnumber (W) to indicate a number of encoded data slices per set that mustbe accurately stored before the encoded data segment is deemed to havebeen properly stored. The dispersed storage error encoding parametersmay further include slicing information (e.g., the number of encodeddata slices that will be created for each data segment) and/or slicesecurity information (e.g., per encoded data slice encryption,compression, integrity checksum, etc.).

In the present example, Cauchy Reed-Solomon has been selected as theencoding function (a generic example is shown in FIG. 4 and a specificexample is shown in FIG. 5); the data segmenting protocol is to dividethe data object into fixed sized data segments; and the per data segmentencoding values include: a pillar width of 5, a decode threshold of 3, aread threshold of 4, and a write threshold of 4. In accordance with thedata segmenting protocol, the computing device 12 or 16 divides dataobject 40 into a plurality of fixed sized data segments (e.g., 1 throughY of a fixed size in range of Kilo-bytes to Tera-bytes or more). Thenumber of data segments created is dependent of the size of the data andthe data segmenting protocol.

The computing device 12 or 16 then disperse storage error encodes a datasegment using the selected encoding function (e.g., Cauchy Reed-Solomon)to produce a set of encoded data slices. FIG. 4 illustrates a genericCauchy Reed-Solomon encoding function, which includes an encoding matrix(EM), a data matrix (DM), and a coded matrix (CM). The size of theencoding matrix (EM) is dependent on the pillar width number (T) and thedecode threshold number (D) of selected per data segment encodingvalues. To produce the data matrix (DM), the data segment is dividedinto a plurality of data blocks and the data blocks are arranged into Dnumber of rows with Z data blocks per row. Note that Z is a function ofthe number of data blocks created from the data segment and the decodethreshold number (D). The coded matrix is produced by matrix multiplyingthe data matrix by the encoding matrix.

FIG. 5 illustrates a specific example of Cauchy Reed-Solomon encodingwith a pillar number (T) of five and decode threshold number of three.In this example, a first data segment is divided into twelve data blocks(D1-D12). The coded matrix includes five rows of coded data blocks,where the first row of X11-X14 corresponds to a first encoded data slice(EDS 1_1), the second row of X21-X24 corresponds to a second encodeddata slice (EDS 2_1), the third row of X31-X34 corresponds to a thirdencoded data slice (EDS 3_1), the fourth row of X41-X44 corresponds to afourth encoded data slice (EDS 4_1), and the fifth row of X51-X54corresponds to a fifth encoded data slice (EDS 5_1). Note that thesecond number of the EDS designation corresponds to the data segmentnumber.

Returning to the discussion of FIG. 3, the computing device also createsa slice name (SN) for each encoded data slice (EDS) in the set ofencoded data slices. A typical format for a slice name 80 is shown inFIG. 6. As shown, the slice name (SN) 80 includes a pillar number of theencoded data slice (e.g., one of 1-T), a data segment number (e.g., oneof 1-Y), a vault identifier (ID), a data object identifier (ID), and mayfurther include revision level information of the encoded data slices.The slice name functions as, at least part of, a DSN address for theencoded data slice for storage and retrieval from the DSN memory 22.

As a result of encoding, the computing device 12 or 16 produces aplurality of sets of encoded data slices, which are provided with theirrespective slice names to the storage units for storage. As shown, thefirst set of encoded data slices includes EDS 1_1 through EDS 5_1 andthe first set of slice names includes SN 1_1 through SN 5_1 and the lastset of encoded data slices includes EDS 1_Y through EDS 5_Y and the lastset of slice names includes SN 1_Y through SN 5_Y.

FIG. 7 is a schematic block diagram of an example of dispersed storageerror decoding of a data object that was dispersed storage error encodedand stored in the example of FIG. 4. In this example, the computingdevice 12 or 16 retrieves from the storage units at least the decodethreshold number of encoded data slices per data segment. As a specificexample, the computing device retrieves a read threshold number ofencoded data slices.

To recover a data segment from a decode threshold number of encoded dataslices, the computing device uses a decoding function as shown in FIG.8. As shown, the decoding function is essentially an inverse of theencoding function of FIG. 4. The coded matrix includes a decodethreshold number of rows (e.g., three in this example) and the decodingmatrix in an inversion of the encoding matrix that includes thecorresponding rows of the coded matrix. For example, if the coded matrixincludes rows 1, 2, and 4, the encoding matrix is reduced to rows 1, 2,and 4, and then inverted to produce the decoding matrix.

FIG. 9 is a schematic block diagram of another embodiment of a dispersedstorage network (DSN) that a district storage and task (DST) processingunit 916, the network 24 of FIG. 1, and a storage set. The DSTProcessing unit can be utilized by computing device 16 of FIG. 1functioning as a dispersed storage processing agent for computing device14 as described previously. The DST processing unit 916 can include theDST client module 34 of FIG. 1. The storage set can include set of DSTexecution (EX) units 1-5. Alternatively, the storage set may include anynumber of DST execution units. Hereafter, each DST execution unit may beinterchangeably referred to as a storage unit and the storage set may beinterchangeably referred to as a set of storage units. The DSN functionsto encode data for storage in the DSN.

In many instances, such as Trimmed Writes, Foster Slices, and/or caseswhen it is known that storage units are down/unavailable/not keeping upwith performance, it can be known prior to the time of the write, orprior to the time the slices are computed, that it will not be possibleto store some of the slices. In these instances, computational resourcescan be saved by not computing the full width number of slices, butinstead performing a vector-vector multiplication of a vector containingthe data elements, and a vector from the encoding matrix correspondingto a slice that is known will be stored. Vectors of the encoding matrixcorresponding to slices that will not be written are not multipliedagainst the data vector. This enables the DST processing unit to computeparticular slices on demand, at the time they need to be written,thereby saving the DST processing unit from having to compute the entirewidth number of slices, as some of which might never be written or needto be written. This same strategy may be used by rebuild modules torecover only those slices that need to be rebuilt.

In an example of operation of the encoding of a data object for storage,for each of the available storage units of the set of storage units, theDST Processing Unit can eliminate a corresponding row of an encodingmatrix to produce a shortened encoding matrix, where a number ofremaining rows of the shortened encoding matrix includes at least aminimum threshold number of rows (e.g., a decode threshold number, awrite threshold number). To accomplish this, the DST processing unit canobtain storage unit status of each storage unit of the set of storageunits to identify at least one unavailable storage unit, for example, byrequesting information from the storage units, performing a lookup,and/or interpreting results of a test or a previous access scenario. TheDST processing unit can obtain an encoding matrix, for example, byinterpreting system registry information. The DST processing unit canthen eliminate the row of the encoding matrix that corresponds to theunavailable storage unit.

In various embodiments, there may not be enough available storage unitsto achieve a minimum threshold number of rows in the shortened encodingmatrix. The DST storage unit can compare the number of rows in theshortened encoding matrix to the decode threshold number and/or thewrite threshold number, or compare the number of available storage unitsto the decode threshold number and/or write threshold number beforecreating the shortened encoding matrix. If there are not enoughavailable storage units, the DST processing unit can forego storage ofthe data object. In various embodiments, the DST processing unit cansend a notification back to an entity that sent the data object forstorage, indicating that the number of available storage units is lowand that the data will not be stored at that time. In variousembodiments, the DST processing unit will wait for a fixed timeoutperiod, check the storage unit availability again, and then proceed withstorage if there are enough available storage units. In variousembodiments, the DST processing unit will automatically receivereal-time updates indicating if storage units are available, and canwait until the number of available storage units meets the thresholdminimum before storing the data object.

In various embodiments, having produced the shortened encoding matrix,the received data object can be divided into at least one data segmentas previously discusses. For each of these data segments, the DSTprocessing unit can multiply the shortened encoding matrix by a datamatrix to produce a coded matrix as discussed previously, using theshortened encoding matrix instead of the usual encoding matrix. The datamatrix can be produced by encoding a data segment into a plurality ofdata blocks as discussed previously. The DST processing unit can obtainthe data segment, encode the data segment into the plurality of datablocks to produce the data matrix, and perform matrix multiplication onthe shortened encoding matrix and the data matrix to produce the codedmatrix.

In various embodiments, having produced a coded matrix corresponding toeach data segment, the DST processing unit can extract encoded dataslices from each coded matrix. For example, the DST processing unit caninterpret each row of each coded matrix as a unique encoded data slice.Having extracted the encoded data slices, for each extracted encodeddata slice, the DST processing unit can send, via the network 24, theextracted encoded data slice to a corresponding storage unit forstorage. For example, the DST processing unit sends encoded data slice 1to DST execution unit 1, encoded data slice 3 to DST execution unit 3,etc.

FIG. 10 is a diagram illustrating an example of matrix multiplication ofa shortened encoding matrix and a data matrix (D) using a dispersedstorage error encoding function to produce a coded matrix (C), where agroup of encoded data slices are produced from the coded matrix. In anexample of operation of using a Reed Solomon encoding function, a datasegment is converted into data blocks (e.g., D1-D12) of a portion of adata matrix (D). A row of an encoding matrix is eliminated to produce ashortened encoding matrix 1010, where the eliminated row corresponds toan unavailable storage unit. For example, a second row of the encodingmatrix is eliminated when a second storage unit of a set of five storageunits is unavailable. In various embodiments where multiple storageunits are unavailable, multiple corresponding rows can be eliminated.

The shortened encoding matrix 1010 is matrix multiplied by the datamatrix (D) to produce the coded matrix (C). As a specific example, thedispersed storage error encoding utilizes an error coding number of five(e.g., width of 5) and a decode threshold number of three. The encodingmatrix (E) can include five rows of three coefficients (e.g., a-o). Whenone row is eliminated, the shortened encoding matrix includes 4 rows and3 columns. The data segment can be divided into data blocks D1-12 whichare arranged into the portion of the data matrix (D) having 3 rows of 4data blocks when the number of data blocks is 12. The number of rows ofthe data matrix matches the number of columns of the shortened encodingmatrix (e.g., the decode threshold number). The number of columns of thedata matrix increases as the number of data blocks of the data segmentincreases. The data matrix can be matrix multiplied by the shortenedencoding matrix to produce the coded matrix, which includes 4 rows of 4encoded data blocks (e.g., X11-X14, X31-X34, X41-X44, and X51-X54). Thenumber of rows of the coded matrix matches the number of rows of theshortened encoding matrix (e.g., the error coding number). For instance,X11=aD1+bD5+cD9; X12=aD2+bD6+cD10; X34=gD4+hD8+iD12; andX54=mD4+nD8+oD12.

One or more encoded data blocks from each row of the coded matrix can beselected to form a corresponding encoded data slice of a group ofencoded data slices. For example, coded values X11-X14 are selected toproduce an encoded data slice 1, coded values X31-X34 are selected toproduce an encoded data slice 3, coded values X41-X44 are selected toproduce an encoded data slice 4, and coded values X51-X54 are selectedto produce an encoded data slice 5. The data matrix (e.g., the datasegment) can be recovered (e.g., to produce a recovered data segment)when any decode threshold number of corruption-free error coded dataslices are available of the group of error coded data slices.Alternatively, the recovered data segment may be reproduced when adecode threshold number of encoded data blocks for each column of thecoded matrix are available.

In various embodiments, a processing system of a dispersed storage andtask (DST) processing unit includes at least one processor and a memorythat stores operational instructions, that when executed by the at leastone processor cause the processing system to receive a data object forstorage in the DSN via a network. Available storage unit data isgenerated, indicating a subset of a plurality of storage units of theDSN that corresponds to a plurality of available storage units. Ashortened encoding matrix is generated based on an original encodingmatrix and the available storage unit data. A size of the shortenedencoding matrix is based on a number of storage units in the pluralityof available storage units. A plurality of encoded slices is generated,each for transmission to one of the plurality of available storage unitsvia the network, by performing an encoding function on the shortenedencoding matrix and the data object.

In various embodiments, the plurality of available storage units is aproper subset of the plurality of storage units. The shortened encodingmatrix is generated by eliminating at least one row from the originalencoding matrix. The at least one row corresponds to at least oneunavailable storage unit not included in the subset. In variousembodiments, the shortened encoding matrix includes at least a number ofrows corresponding a decode threshold number and/or a write thresholdnumber. In various embodiments, generating the available storage unitdata includes comparing the number of storage units in the plurality ofavailable storage units to a decode threshold number and/or a writethreshold number. The shortened encoding matrix and plurality of encodedslices are generated when the available storage unit data indicates thatthe number of storage units in the plurality of available storage unitsis greater than or equal to the decode threshold number and/or the writethreshold number. In various embodiments, a low storage unitavailability notification is generated for transmission via the networkwhen the available storage unit data indicates that the number ofstorage units in the plurality of available storage units is less thanthe decode threshold number and/or the write threshold number,indicating that the DST processing unit will forego storage of the dataobject.

In various embodiments, generating the plurality of encoded slicesincludes dividing the data object into at least one data segment,generating a data matrix corresponding to each data segment, multiplyingeach data matrix by the shorting encoding matrix to produce at least onecoded matrix, and extracting the plurality of encoded slices from the atleast one coded matrix.

In various embodiments, storage unit status data is received via thenetwork. The available storage unit data is generated based on thestorage unit status data. In various embodiments, a plurality of statusrequests are generated for transmission to a plurality of storage units.The storage unit status data is received from the plurality of storageunits in response to the plurality of status requests. In variousembodiments, generating the available storage unit data includesinterpreting results of a test and/or interpreting results of a previousaccess.

FIG. 11 is a flowchart illustrating an example of encoding data forstorage. In particular, a method is presented for use in associationwith one or more functions and features described in conjunction withFIGS. 1-9, for execution by a dispersed storage and task (DST)processing unit that includes a processor or via another processingsystem of a dispersed storage network that includes at least oneprocessor and memory that stores instruction that configure theprocessor or processors to perform the steps described below. Step 1102includes receiving a data object for storage in a distributed storagenetwork (DSN) via a network. Step 1104 includes generating availablestorage unit data indicating a subset of a plurality of storage units ofthe DSN that corresponds to a plurality of available storage units. Step1106 includes generating a shortened encoding matrix based on anoriginal encoding matrix and the available storage unit data, where asize of the shortened encoding matrix is based on a number of storageunits in the plurality of available storage units. Step 1108 includesgenerating a plurality of encoded slices, each for transmission to oneof the plurality of available storage units via the network, byperforming an encoding function on the shortened encoding matrix and thedata object.

In various embodiments, the plurality of available storage units is aproper subset of the plurality of storage units. The shortened encodingmatrix is generated by eliminating at least one row from the originalencoding matrix. The at least one row corresponds to at least oneunavailable storage unit not included in the subset. In variousembodiments, the shortened encoding matrix includes at least a number ofrows corresponding a decode threshold number and/or a write thresholdnumber. In various embodiments, generating the available storage unitdata includes comparing the number of storage units in the plurality ofavailable storage units to a decode threshold number and/or a writethreshold number. The shortened encoding matrix and plurality of encodedslices are generated when the available storage unit data indicates thatthe number of storage units in the plurality of available storage unitsis greater than or equal to the decode threshold number and/or the writethreshold number. In various embodiments, a low storage unitavailability notification is generated for transmission via the networkwhen the available storage unit data indicates that the number ofstorage units in the plurality of available storage units is less thanthe decode threshold number and/or the write threshold number,indicating that the DST processing unit will forego storage of the dataobject.

In various embodiments, generating the plurality of encoded slicesincludes dividing the data object into at least one data segment,generating a data matrix corresponding to each data segment, multiplyingeach data matrix by the shorting encoding matrix to produce at least onecoded matrix, and extracting the plurality of encoded slices from the atleast one coded matrix.

In various embodiments, storage unit status data is received via thenetwork. The available storage unit data is generated based on thestorage unit status data. In various embodiments, a plurality of statusrequests are generated for transmission to a plurality of storage units.The storage unit status data is received from the plurality of storageunits in response to the plurality of status requests. In variousembodiments, generating the available storage unit data includesinterpreting results of a test and/or interpreting results of a previousaccess.

In various embodiments, a non-transitory computer readable storagemedium includes at least one memory section that stores operationalinstructions that, when executed by a processing system of a dispersedstorage network (DSN) that includes a processor and a memory, causes theprocessing system to receive a data object for storage in the DSN via anetwork. Available storage unit data is generated, indicating a subsetof a plurality of storage units of the DSN that corresponds to aplurality of available storage units. A shortened encoding matrix isgenerated based on an original encoding matrix and the available storageunit data. A size of the shortened encoding matrix is based on a numberof storage units in the plurality of available storage units. Aplurality of encoded slices is generated, each for transmission to oneof the plurality of available storage units via the network, byperforming an encoding function on the shortened encoding matrix and thedata object.

It is noted that terminologies as may be used herein such as bit stream,stream, signal sequence, etc. (or their equivalents) have been usedinterchangeably to describe digital information whose contentcorresponds to any of a number of desired types (e.g., data, video,speech, audio, etc. any of which may generally be referred to as ‘data’).

As may be used herein, the terms “substantially” and “approximately”provides an industry-accepted tolerance for its corresponding termand/or relativity between items. Such an industry-accepted toleranceranges from less than one percent to fifty percent and corresponds to,but is not limited to, component values, integrated circuit processvariations, temperature variations, rise and fall times, and/or thermalnoise. Such relativity between items ranges from a difference of a fewpercent to magnitude differences. As may also be used herein, theterm(s) “configured to”, “operably coupled to”, “coupled to”, and/or“coupling” includes direct coupling between items and/or indirectcoupling between items via an intervening item (e.g., an item includes,but is not limited to, a component, an element, a circuit, and/or amodule) where, for an example of indirect coupling, the intervening itemdoes not modify the information of a signal but may adjust its currentlevel, voltage level, and/or power level. As may further be used herein,inferred coupling (i.e., where one element is coupled to another elementby inference) includes direct and indirect coupling between two items inthe same manner as “coupled to”. As may even further be used herein, theterm “configured to”, “operable to”, “coupled to”, or “operably coupledto” indicates that an item includes one or more of power connections,input(s), output(s), etc., to perform, when activated, one or more itscorresponding functions and may further include inferred coupling to oneor more other items. As may still further be used herein, the term“associated with”, includes direct and/or indirect coupling of separateitems and/or one item being embedded within another item.

As may be used herein, the term “compares favorably”, indicates that acomparison between two or more items, signals, etc., provides a desiredrelationship. For example, when the desired relationship is that signal1 has a greater magnitude than signal 2, a favorable comparison may beachieved when the magnitude of signal 1 is greater than that of signal 2or when the magnitude of signal 2 is less than that of signal 1. As maybe used herein, the term “compares unfavorably”, indicates that acomparison between two or more items, signals, etc., fails to providethe desired relationship.

As may also be used herein, the terms “processing module”, “processingcircuit”, “processor”, and/or “processing unit” may be a singleprocessing device or a plurality of processing devices. Such aprocessing device may be a microprocessor, micro-controller, digitalsignal processor, microcomputer, central processing unit, fieldprogrammable gate array, programmable logic device, state machine, logiccircuitry, analog circuitry, digital circuitry, and/or any device thatmanipulates signals (analog and/or digital) based on hard coding of thecircuitry and/or operational instructions. The processing module,module, processing circuit, and/or processing unit may be, or furtherinclude, memory and/or an integrated memory element, which may be asingle memory device, a plurality of memory devices, and/or embeddedcircuitry of another processing module, module, processing circuit,and/or processing unit. Such a memory device may be a read-only memory,random access memory, volatile memory, non-volatile memory, staticmemory, dynamic memory, flash memory, cache memory, and/or any devicethat stores digital information. Note that if the processing module,module, processing circuit, and/or processing unit includes more thanone processing device, the processing devices may be centrally located(e.g., directly coupled together via a wired and/or wireless busstructure) or may be distributedly located (e.g., cloud computing viaindirect coupling via a local area network and/or a wide area network).Further note that if the processing module, module, processing circuit,and/or processing unit implements one or more of its functions via astate machine, analog circuitry, digital circuitry, and/or logiccircuitry, the memory and/or memory element storing the correspondingoperational instructions may be embedded within, or external to, thecircuitry comprising the state machine, analog circuitry, digitalcircuitry, and/or logic circuitry. Still further note that, the memoryelement may store, and the processing module, module, processingcircuit, and/or processing unit executes, hard coded and/or operationalinstructions corresponding to at least some of the steps and/orfunctions illustrated in one or more of the Figures. Such a memorydevice or memory element can be included in an article of manufacture.

One or more embodiments have been described above with the aid of methodsteps illustrating the performance of specified functions andrelationships thereof. The boundaries and sequence of these functionalbuilding blocks and method steps have been arbitrarily defined hereinfor convenience of description. Alternate boundaries and sequences canbe defined so long as the specified functions and relationships areappropriately performed. Any such alternate boundaries or sequences arethus within the scope and spirit of the claims. Further, the boundariesof these functional building blocks have been arbitrarily defined forconvenience of description. Alternate boundaries could be defined aslong as the certain significant functions are appropriately performed.Similarly, flow diagram blocks may also have been arbitrarily definedherein to illustrate certain significant functionality.

To the extent used, the flow diagram block boundaries and sequence couldhave been defined otherwise and still perform the certain significantfunctionality. Such alternate definitions of both functional buildingblocks and flow diagram blocks and sequences are thus within the scopeand spirit of the claims. One of average skill in the art will alsorecognize that the functional building blocks, and other illustrativeblocks, modules and components herein, can be implemented as illustratedor by discrete components, application specific integrated circuits,processors executing appropriate software and the like or anycombination thereof

In addition, a flow diagram may include a “start” and/or “continue”indication. The “start” and “continue” indications reflect that thesteps presented can optionally be incorporated in or otherwise used inconjunction with other routines. In this context, “start” indicates thebeginning of the first step presented and may be preceded by otheractivities not specifically shown. Further, the “continue” indicationreflects that the steps presented may be performed multiple times and/ormay be succeeded by other activities not specifically shown. Further,while a flow diagram indicates a particular ordering of steps, otherorderings are likewise possible provided that the principles ofcausality are maintained.

The one or more embodiments are used herein to illustrate one or moreaspects, one or more features, one or more concepts, and/or one or moreexamples. A physical embodiment of an apparatus, an article ofmanufacture, a machine, and/or of a process may include one or more ofthe aspects, features, concepts, examples, etc. described with referenceto one or more of the embodiments discussed herein. Further, from figureto figure, the embodiments may incorporate the same or similarly namedfunctions, steps, modules, etc. that may use the same or differentreference numbers and, as such, the functions, steps, modules, etc. maybe the same or similar functions, steps, modules, etc. or differentones.

Unless specifically stated to the contra, signals to, from, and/orbetween elements in a figure of any of the figures presented herein maybe analog or digital, continuous time or discrete time, and single-endedor differential. For instance, if a signal path is shown as asingle-ended path, it also represents a differential signal path.Similarly, if a signal path is shown as a differential path, it alsorepresents a single-ended signal path. While one or more particulararchitectures are described herein, other architectures can likewise beimplemented that use one or more data buses not expressly shown, directconnectivity between elements, and/or indirect coupling between otherelements as recognized by one of average skill in the art.

The term “module” is used in the description of one or more of theembodiments. A module implements one or more functions via a device suchas a processor or other processing device or other hardware that mayinclude or operate in association with a memory that stores operationalinstructions. A module may operate independently and/or in conjunctionwith software and/or firmware. As also used herein, a module may containone or more sub-modules, each of which may be one or more modules.

As may further be used herein, a computer readable memory includes oneor more memory elements. A memory element may be a separate memorydevice, multiple memory devices, or a set of memory locations within amemory device. Such a memory device may be a read-only memory, randomaccess memory, volatile memory, non-volatile memory, static memory,dynamic memory, flash memory, cache memory, and/or any device thatstores digital information. The memory device may be in a form a solidstate memory, a hard drive memory, cloud memory, thumb drive, servermemory, computing device memory, and/or other physical medium forstoring digital information.

While particular combinations of various functions and features of theone or more embodiments have been expressly described herein, othercombinations of these features and functions are likewise possible. Thepresent disclosure is not limited by the particular examples disclosedherein and expressly incorporates these other combinations.

What is claimed is:
 1. A method for execution by a dispersed storage andtask (DST) processing unit that includes a processor, the methodcomprises: receiving a data object for storage in a distributed storagenetwork (DSN) via a network; generating available storage unit dataindicating a subset of a plurality of storage units of the DSN thatcorresponds to a plurality of available storage units; generating ashortened encoding matrix based on an original encoding matrix and theavailable storage unit data, wherein a size of the shortened encodingmatrix is based on a number of storage units in the plurality ofavailable storage units; and generating a plurality of encoded slices,each for transmission to one of the plurality of available storage unitsvia the network, by performing an encoding function on the shortenedencoding matrix and the data object.
 2. The method of claim 1, whereinthe plurality of available storage units is a proper subset of theplurality of storage units, wherein shortened encoding matrix isgenerated by eliminating at least one row from the original encodingmatrix, and wherein the at least one row corresponds to at least oneunavailable storage unit not included in the subset.
 3. The method ofclaim 1, wherein the shortened encoding matrix includes at least anumber of rows corresponding to one of: a decode threshold number or awrite threshold number.
 4. The method of claim 1, wherein generating theavailable storage unit data includes comparing the number of storageunits in the plurality of available storage units to at least one of: adecode threshold number or a write threshold number, and wherein theshortened encoding matrix and plurality of encoded slices are generatedwhen the available storage unit data indicates that the number ofstorage units in the plurality of available storage units is greaterthan or equal to the at least one of: the decode threshold number or thewrite threshold number.
 5. The method of claim 4, further comprisinggenerating a low storage unit availability notification for transmissionvia the network when the available storage unit data indicates that thenumber of storage units in the plurality of available storage units isless than the at least one of: the decode threshold number or the writethreshold number, indicating that the DST processing unit will foregostorage of the data object.
 6. The method of claim 1, wherein generatingthe plurality of encoded slices includes dividing the data object intoat least one data segment, generating a data matrix corresponding toeach data segment, multiplying each data matrix by the shorting encodingmatrix to produce at least one coded matrix, and extracting theplurality of encoded slices from the at least one coded matrix.
 7. Themethod of claim 1, further comprising receiving storage unit status datavia the network, wherein generating the available storage unit data isbased on the storage unit status data.
 8. The method of claim 7, furthercomprising generating a plurality of status requests for transmission toa plurality of storage units, and wherein the storage unit status datais received from the plurality of storage units in response to theplurality of status requests.
 9. The method of claim 1, whereingenerating the available storage unit data includes at least one of:interpreting results of a test or interpreting results of a previousaccess.
 10. A processing system of a dispersed storage and task (DST)processing unit comprises: at least one processor; a memory that storesoperational instructions, that when executed by the at least oneprocessor cause the processing system to: receive a data object forstorage in a distributed storage network (DSN) via a network; generateavailable storage unit data indicating a subset of a plurality ofstorage units of the DSN that corresponds to a plurality of availablestorage units; generate a shortened encoding matrix based on an originalencoding matrix and the available storage unit data, wherein a size ofthe shortened encoding matrix is based on a number of storage units inthe plurality of available storage units; and generate a plurality ofencoded slices, each for transmission to one of the plurality ofavailable storage units via the network, by performing an encodingfunction on the shortened encoding matrix and the data object.
 11. Theprocessing system of claim 10, wherein the plurality of availablestorage units is a proper subset of the plurality of storage units,wherein shortened encoding matrix is generated by eliminating at leastone row from the original encoding matrix, and wherein the at least onerow corresponds to at least one unavailable storage unit not included inthe subset.
 12. The processing system of claim 10, wherein the shortenedencoding matrix includes at least a number of rows corresponding to oneof: a decode threshold number or a write threshold number.
 13. Theprocessing system of claim 10, wherein generating the available storageunit data includes comparing the number of storage units in theplurality of available storage units to at least one of: a decodethreshold number or a write threshold number, and wherein the shortenedencoding matrix and plurality of encoded slices are generated when theavailable storage unit data indicates that the number of storage unitsin the plurality of available storage units is greater than or equal tothe at least one of: the decode threshold number or the write thresholdnumber.
 14. The processing system of claim 13, wherein the operationalinstructions, when executed by the at least one processor, further causethe processing system to generate a low storage unit availabilitynotification for transmission via the network when the available storageunit data indicates that the number of storage units in the plurality ofavailable storage units is less than the at least one of: the decodethreshold number or the write threshold number, indicating that the DSTprocessing unit will forego storage of the data object.
 15. Theprocessing system of claim 10, wherein generating the plurality ofencoded slices includes dividing the data object into at least one datasegment, generating a data matrix corresponding to each data segment,multiplying each data matrix by the shorting encoding matrix to produceat least one coded matrix, and extracting the plurality of encodedslices from the at least one coded matrix.
 16. The processing system ofclaim 10, wherein the operational instructions, when executed by the atleast one processor, further cause the processing system to receivestorage unit status data via the network, wherein generating theavailable storage unit data is based on the storage unit status data.17. The processing system of claim 16, wherein the operationalinstructions, when executed by the at least one processor, further causethe processing system to generate a plurality of status requests fortransmission to a plurality of storage units, and wherein the storageunit status data is received from the plurality of storage units inresponse to the plurality of status requests.
 18. The processing systemof claim 10, wherein generating the available storage unit data includesat least one of: interpreting results of a test or interpreting resultsof a previous access.
 19. A non-transitory computer readable storagemedium comprises: at least one memory section that stores operationalinstructions that, when executed by a processing system of a dispersedstorage network (DSN) that includes a processor and a memory, causes theprocessing system to: receive a data object for storage in the DSN via anetwork; generate available storage unit data indicating a subset of aplurality of storage units of the DSN that corresponds to a plurality ofavailable storage units; generate a shortened encoding matrix based onan original encoding matrix and the available storage unit data, whereina size of the shortened encoding matrix is based on a number of storageunits in the plurality of available storage units; and generate aplurality of encoded slices, each for transmission to one of theplurality of available storage units via the network, by performing anencoding function on the shortened encoding matrix and the data object.20. The non-transitory computer readable storage medium of claim 19,wherein the plurality of available storage units is a proper subset ofthe plurality of storage units, wherein shortened encoding matrix isgenerated by eliminating at least one row from the original encodingmatrix, and wherein the at least one row corresponds to at least oneunavailable storage unit not included in the subset.